QTM 385 - Experimental Methods

Lecture 16 - Interference and Spillovers

Danilo Freire

Emory University

How are you doing? 😊

Brief recap 📚

Brief recap 📚

  • Natural experiments framework:
    • True vs “as-if” randomness in treatment assignment
    • Core assumption: exogeneity of assignment mechanism
    • Examples: Lottery-based charter school studies, border discontinuity designs
  • Quasi-experimental approaches:
    • Regression discontinuity (RDD): Leveraging threshold-based assignment
    • Difference-in-differences (DID): Utilising parallel trends assumption
  • Methodological challenges:
    • Selection bias in observational data
    • SUTVA violations from treatment spillovers
    • Power limitations in natural variation contexts
  • Empirical examples:
    • Angrist et al. (2013): School lottery IV analysis
    • Card & Krueger (1994): Minimum wage DID study
    • Mignozzetti et al. (2024): RDD in legislative analysis
  • Validation strategies:
    • Placebo tests for assumption verification
    • Pre-treatment trend analysis for DID
    • Robustness checks for sensitivity assessments
  • Ethical considerations:
    • Responsible communication of limitations
    • Secondary data ethics compliance
    • Policy impact assessments for natural experiments

Today’s plan 📅

Interference and spillovers

Interference

Interference

When treatment effects spill over

  • Remember SUTVA?
    • Stable unit treatment value assumption
  • The stable part means that potential outcomes should be independent of the treatment
  • As you can imagine, this poses risks to causal identification
  • This happens quite often in social and public health interventions:
    • Peer effects in education
    • Contagion in public health
    • Spillovers in policy evaluations
    • Network effects in marketing and technology